Factors influencing survival of Canada geese breeding in Southern Quebec
Bibliographic record
Abstract
ABSTRACT Temperate nesting Canada geese are considered a nuisance in many regions of eastern North America. In southern Quebec, a breeding population became established 20 years ago and has grown steadily since that time. Because of the long‐lived nature of geese, understanding the factors that influence annual survival is critical to the management of these populations. Our objectives were to describe the spatiotemporal distribution of the harvest of Canada geese that breed in southern Quebec, determine how year, sex, and age affect survival rates, and to evaluate the effects of hatch date and body condition near fledging on juvenile survival. We conducted mixed live recapture and dead recovery capture‐mark‐recapture analyses using data from birds banded as pre‐fledged juveniles between 2003 and 2009 ( n = 3,972). Recoveries were distributed near the breeding area and along the east coast of the United States. Juveniles were mainly recovered in Quebec and yearlings in the United States. Harvest during the special early hunting season in Quebec represented only 9% of the total harvest. Annual survival rates were similar for both males and females, but varied among years for each age class. Survival averaged 0.82 (95% CI 0.76–0.87) for juveniles, 0.76 (0.69–0.82) for yearlings, and 0.82 (0.75–0.87) for adults. We observed a negative relationship between hatch date and juvenile survival but did not find significant effects of body condition and age at banding on survival. In addition to a short migration, a possible explanation for the high survival of juveniles includes the use by family groups predominantly of areas that are not open to hunting. The use of rural habitats where susceptibility to hunting is high, combined with the behavior of molt migration could explain the lower survival rates of yearlings than juveniles. We argue that high survival rates for all age classes contribute significantly to the growth of this population. © 2014 The Wildlife Society.
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How this classification was reachedexpand
Full frame machine prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.
Distilled classifier scores by category (both heads)
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.000 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.002 | 0.000 |
Machine scores (provisional)
The two teacher heads of the student model, read on this work. A score orders the frame for review; it never asserts a category, and the validation status ships verbatim with every row.
Baseline scores from an immature model (maturity gate not passed, 7 training rounds). Scores rank; they never assert a category.
score_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from itClassification
machine, unvalidatedMachine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.
How this classification was reached, model by model and score by score, is at the end of the page under "How this classification was reached".